An Evaluation of the Reliability of the Results Obtained by the LBET, QSDFT, BET, and DR Methods for the Analysis of the Porous Structure of Activated Carbons

Abstract

This paper presents the results of an analysis of the impact of the activator to the product of carbonized materials mass ratio on the porous structure of activated carbons obtained from mahogany, ebony, and hornbeam wood by carbonization and chemical activation with potassium hydroxide. The analyses were carried out on nitrogen adsorption isotherms using the Brunauer–Emmett–Teller (BET), Dubinin-Radushkevitch (DR), and Quenched Solid Density Functional Theory (QSDFT) methods, as well as the numerical clustering-based adsorption analysis (LBET) method. The activated carbons with the best adsorption properties and homogeneous surfaces were obtained at a mass ratio of R = 3. The analyses suggest the significant potential of producing adsorbents characterized by a large surface area and adsorptive capacity from raw materials such as mahogany, ebony, and hornbeam wood. The analyses in question also included an evaluation of the usability and reliability of the results obtained with the employed methods of structural analysis. Particular focus was placed on the limitations of adsorption models and on critically analyzing the output data. Our study shows the unique advantages of the LBET method compared to the other methods used. The LBET method allowed us, for example, to determine the degree of heterogeneity of the surface of the studied activated carbons and the shape of the clusters of adsorbate molecules formed in the pores of the studied material, as well as obtain information about the distribution of adsorption energy on the first adsorbed layer. This study also demonstrates the limitations of the methods used and the necessity to use LBET and QSDFT methods simultaneously for porous structural analysis. The simultaneous analysis of the adsorption isotherms via the LBET and the QSDFT methods makes it possible to choose the optimal preparation conditions while considering the properties of the original raw material. The analyses also suggest the complementary character of the employed methods and the scope of the useful and reliable information that can be obtained with these methods.

Analysis of the Effect of Conditions of Preparation of Nitrogen-Doped Activated Carbons Derived from Lotus Leaves by Activation with Sodium Amide on the Formation of Their Porous Structure

“…However, the results of analyses carried out using BET, T-plot, DR and DFT [ 31 ] methods do not fully explain the processes occurring during the preparation of activated carbons under various preparation conditions. Therefore, in this work, the LBET method [ 39 , 40 , 41 , 42 , 43 , 44 ] was used to analyze nitrogen adsorption isotherms on activated carbons prepared from the products of carbonization of lotus leaves. The results of nitrogen isothermal adsorption isothermal analysis using the above mentioned method are presented in Table 2 and Figure 2 .…”

“…The LBET method as well as its theoretical basis have been described in the author’s previous publications [ 39 , 40 , 41 , 42 , 43 , 44 ], therefore, it will not be described in this article. It should be mentioned, however, that the LBET models have five parameters: the volume of the first adsorbed layer V hA (cm 3 /g), the dimensionless energy parameter for the first adsorbed layer— Q A / RT , the geometrical parameter of the porous structure determining the height of the adsorbate molecule clusters α , the geometrical parameter of the porous structure determining the width of the adsorbate molecule clusters β and the dimensionless energy parameter for the higher adsorbed layers B C which can be adjusted by fitting LBET equation to the adsorption isotherm, with a chosen variant of the surface energy distribution function [ 39 , 40 , 41 , 42 , 43 , 44 ].…”

Computer Analysis of the Effect of Activation Temperature on the Microporous Structure Development of Activated Carbon Derived from Common Polypody

“…Considering the pros and cons of the BET theory and the BET multilayer adsorption equation derived therefrom, work was undertaken to develop a new clustering-based adsorption theory based on the fundamentals behind the BET theory and informed by the process of multilayer adsorption on the surface of microporous carbonaceous materials [ 30 , 31 , 32 ]. The work on the new theory, named uniBET, was based on the principal assumption that it is not possible to unambiguously and credibly determine the distribution of energy on the surface of an adsorbent and the structure of a porous material, yet a mathematical description of the adsorption process should take into account the anticipated geometrical properties of the material and those related to energy on its surface [ 30 , 31 , 32 ]. That theory served as the basis for developing new adsorption models, as well as a unique procedure for the fast multivariant identification of adsorption systems.…”

“…That theory served as the basis for developing new adsorption models, as well as a unique procedure for the fast multivariant identification of adsorption systems. Together, these are named the new numerical clustering based adsorption analysis (LBET) method [ 30 , 31 , 32 ]. The LBET models involve five parameters: V hA is the volume of the first adsorbed layer; Q A / RT is the dimensionless energy parameter for the first adsorbed layer; B C is the dimensionless energy parameter for the higher adsorbed layers; α is the geometrical parameter of the porous structure determining the height of the adsorbate molecule clusters; β is the average number of sites provided by ( n− 1)th adsorbed layer for the n th layer, averaged over all adsorbate molecule clusters ( β = 1 for narrow pores, β > 1 for wider ones); Z A is the effective contact correction factor; h is the surface heterogeneity parameter; σ e is the fitting error dispersion; and w id is the identification reliability indices, which can be adjusted by fitting of the LBET formula to the adsorption isotherm with a chosen variant of the surface energy distribution function [ 30 , 31 , 32 ].…”

“…To apply the LBET equations for near and supercritical temperatures, an original fluid state model was developed that was fitted with high accuracy compression factor data [ 33 ]. The new numerical clustering-based adsorption analysis method with the implemented LBET class models and the fast multivariant procedure of identification of adsorption systems have been presented in detail in earlier papers [ 30 , 31 , 32 , 33 ].…”